Air quality changes in Cambridge and COVID-19 lockdowns

This document presents some analysis on the recent changes in air pollutants recorded by air quality monitoring sites across Cambridge.

Let’s start by looking at where the data come from.

The map above shows the locations of the air quality monitoring sites in Cambridge. They are:

## # A tibble: 4 x 4
##   site                     code  latitude longitude
##   <chr>                    <chr>    <dbl>     <dbl>
## 1 Cambridge Parker Street  CAM1      52.2     0.126
## 2 Cambridge Gonville Place CAM3      52.2     0.128
## 3 Cambridge Newmarket Road CAM4      52.2     0.142
## 4 Cambridge Montague Road  CAM5      52.2     0.137
## # A tibble: 1 x 5
##   site               code  latitude longitude site_type    
##   <chr>              <chr>    <dbl>     <dbl> <chr>        
## 1 Cambridge Roadside CAM       52.2     0.124 Urban Traffic

Note, that the AURN site (Cambridge Roadside) is the Cambridge Council Building site on Regent Street.

Analysis of the data over several years

The DEFRA AURN site outside the Council offices on Regent Street has data for over a decade but the other sites on the map only have data available for analysis from 2014.

These data are plotted below for three main air pollutants:

  1. Nitrogen dioxide (NO\(_2\)). This is a gaseous compound that comes from the combustion of fossil-fuels. It is very reactive in the atmosphere and has a lifetime of much less than a day. During the day sunlight breaks down NO\(_2\) and at night time reactions with ozone (O\(_3\)) convert NO\(_2\) into the nitrate radical (NO\(_3\)).

  2. Particulate matter less than 10 microns in diameter (PM10) PM10 is an aerosol (a solid/liquid suspended in a gas) which comes from a large number of sources such as dust from roads, sea spray, combustion, construction work, break wear etc. PM10 tends to have a lifetim much longer than a day and gets washed out by things like rain.

  3. Particulate matter less than 2.5 microns in diameter (PM2.5) PM2.5 is a very fine (small) aerosol. This has been shown through many epidemiological studies to be a very important air pollutant. Sources of PM2.5 include primary (direct emissions of particles) and secondary (conversion of gases to particles and sticking together of very small particles)

The long term time-series for NO\(_2\) is shown above. A few key points stick out:

  1. Parker Street has the heighest levels of NO\(_2\) measured in Cambridge.

  2. There has been a long term decrease in NO\(_2\) in Cambridge over time.

  3. There is significant variability in NO\(_2\) from week to week (the spikes in the data).

In the plots above weekly-average data are shown with a smoothed running average (LOESS) added to highlight trends. If you stare at the data you will see that there is a repeating seasonal-cycle, where NO\(_2\) levels peak in the winter and drop to a minimum in the summer. This type of behaviour is very typical for NO\(_2\) and is seen in most places around the world. The causes are a combination of meteorology and chemistry.

The downwards trends in NO\(_2\) are likely to be driven by emission changes, particularly related to vechicle fleet changes and better catalytic converters in vehicles.

## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

The plot above shows the trends in PM10 since 2014. As with the NO\(_2\) time-series plot, there are some trends (shown in the smoothed fits) but these are much smaller than with NO\(_2\).

There are fewer sites measuring PM10 than NO\(_2\) but the sites that measure PM10 tend to agree on the tiimg of spikes in the data. This partly reflects the long lifetime of PM10 and the fact that the sources of PM10 are not local (unlike NO\(_2\) which has major local sources, particular vehicle emissions).

## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

Finally, the plot above focuses on the finer aerosol, PM2.5. In general the picture is similar to the picture with PM10 in that the sites that measure PM2.5 show high levels of correlation in time – highlighting the importance of sources of PM2.5 away from the measurement sites.

Next we focus on the changes that have occured in 2020 – particulalrly during the COVID-19 lockdown period.

Changes in air quality during the lockdown

First let’s look at the changes in NO\(_2\) during the lockdown. The plots above show NO\(_2\) at each of the sites that measure it during 2020 and compare the daily average values (the noisy lines) with the average you would expect based on analysis of data from 2017-2019 (three years).